Table of Contents

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  1. Preface
  2. Introduction to Big Data Management Administration
  3. Big Data Management Engines
  4. Authentication and Authorization
  5. Running Mappings on a Cluster with Kerberos Authentication
  6. Configuring Access to an SSL/TLS-Enabled Cluster
  7. Cluster Configuration
  8. Cluster Configuration Privileges and Permissions
  9. Cloud Provisioning Configuration
  10. Queuing
  11. Tuning for Big Data Processing
  12. Connections
  13. Multiple Blaze Instances on a Cluster

Big Data Management Administrator Guide

Big Data Management Administrator Guide

Fine-Grained SQL Authorization for Hive

Fine-Grained SQL Authorization for Hive

SQL standards-based authorization enables database administrators to impose fine-grained authorization on Hive tables and views when you read data from a Hive source or a target.
Informatica supports fine-grained SQL authorization for Hive sources with Blaze engine, and Hive sources and targets with Spark engines. You can use the Ranger authorization plug-in when you enable fine-grained SQL authorization for mappings that run on a Hortonworks HDP cluster.
You can use the Sentry authorization plug-in when you enable fine-grained SQL authorization for mappings that run on a Cloudera cluster. When the mapping accesses Hive sources in Blaze engine and Hive sources and targets in Spark engine on a cluster that uses Sentry authorization and runs in native mode, you can use fine-grained SQL authorization on the column level if you configure hive.server2.proxy.user in the Hive JDBC connect string.
In this case, the mapping uses the hive.server2.proxy.user value to access Hive sources and targets. When you also configure the mappingImpersonationUserName property, then the mapping uses the mappingImpersonationUserName value to access Hive sources and targets.
You can configure a Hive connection to observe fine-grained SQL authorization.

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